Shift Work – Compare and Critique the Methodology

In a bid to meet the increased work demands, a significant number of organizations have adopted the 24/7 mode of operations. This means that despite everything, work never seizes in such organizations. This then calls for staff to work odd hours, often in shifts, to handle the increased workload effectively. It is little wonder that shift work has attracted a lot of scholarly interest. Specifically, the effect that such work has on health has been researched by scholars such as Karlson et al. (2009), Reinberg and Ashkenazi (2008), Shen et al. (2006), Zhao and Turner (2008), and Tamagawa, Lobb, and Booth (2007) among others.

Summary of the articles

Karlson et al. (2009) conducted research on 118 people working in a hospital setting to study how the shift schedules affected their self-reported health status, fatigue levels, and sleep. Specifically, the researchers wanted to find how a change in the shift schedule would affect the workers. As such, the controlled sample of 118 shift workers who initially worked on a fast forward-rotating schedule, were placed on a slowly backward-rotating schedule. The study sample also included 67 daytime workers. The inclusion of the two categories of workers was meant to provide an insight into the differences in health, fatigue, and sleep deprivation between the two groups. Notably, however, Karlson et al. (2009) assert that the inclusion of the two categories of workers in the study was not meant to provide a comparison on “the degree of health problems associated with shift work with those associated with daytime work” (p. 107). Rather, the researchers state that the inclusion was meant to “examine the changes resulting from schedule intervention” (p. 107). The researchers developed different measures to assess sleep and fatigue, work-family interference, and subjective health. After analyzing the results of their study, they concluded that, just as they had hypothesized, changing shifts to slowly backward-rotating schedules from the fast forward-rotating schedules and including intermediate off days between different shift blocks, resulted in improved subjective health complaints, recovery from fatigue, and sleep in the sampled group.

The main weakness of the study conducted by Karlson et al. (2009) lies in the fact that the researchers could not pinpoint the exact schedule components, which led to the observed improvement in the sleep, fatigue levels, and subjective health conditions in the sampled group. Variables such as age and gender were also not factored in the research.

Still on the shift work subject, Reinberg and Ashkenazi (2008) collected data from a sample made up of 48 male shift workers, with an aim of investigating the link between shift work intolerance and ‘desynchronization’ of circadian rhythms. Of the 48 survey participants, 14 had good tolerance to shift work, 19 had poor tolerance levels, while the remaining 15 respondents had very poor tolerance levels. Medical complaints that shift workers had presented with one year prior to the research, were used as the main indicator of how well a shift worker was able to handle the demands of his work. The research period lasted 15 days, during which the selected sample were exposed to eight-hour shifts.

The researchers used oral temperatures, grip strength and sleep awake-cycles as their main measurement tools. Age was also a variable that Reinberg and Ashkenazi (2008) considered in the research. In their conclusion, Reinberg and Ashkenazi (2008) reported that non-tolerant shift workers exhibited high sensitivity levels to the “desynchronization of their circadian time organization” (p. 626). However, age did not appear to have any affect on the shift worker’s tolerance levels. This observation is however contradicted by Swenson, Waseleski and Hartl (2008), who state that young officers in their 20s and 30s were able to adjust to and tolerate shift work, more than their counterparts aged 40 or more years.

Reinberg and Ashkenazi (2008) further observe that shift work intolerance can be identified through clinical symptoms presented by the workers. Unfortunately, the researchers observe that non-tolerance to shift work can only be determined through the clinical symptoms, which become manifest after workers have been exposed to shift schedules. As such, the question of how best to determine the worker’s non-tolerance to shift work beforehand remains unanswered.

In a survey conducted on 489 workers, Shen et al. (2006) sought to determine if indeed shift work affects sleepiness and fatigue differently. To attain this research objective, the researchers included the “Fatigue Severity Scale (FSS) and the Epworth Sleepiness Scale” in subjective, self-report questionnaires administered to the identified research sample (Shen et al., 2006, p. 1). The researcher categorized the sample depending on whether they ever took part in shift work. Shift workers were then categorized according to the frequency of their schedules. This means that the researcher had a study sample that consisted of people who had never worked on shift, those whose involvement was less than four times a month, those whose shift work was 1 to 2 days a week, and those whose shift work was three or more days a week.

After analyzing the results using a combination on Anova, Ancova, Post Hoc tests and Pearson’s correlation tests, Shen et al. (2006) concluded that shift work affected subjective fatigue, but not subjective sleepiness. As such, they suggested that sleep and fatigue in relation to shift work should be treated as independent and distinct concepts in future. They also acknowledged that the frequency of shift worker could determine whether workers experience negative health consequences or reduced job-performance capacity. Despite their observations, Shen et al. (2006) failed to determine how shift work leads to an increase in subjective fatigue.

In a study meant to investigate whether personality traits affected worker’s tolerance to shift work, Tamagawa et al. (2007) sampled 54 police officers who worked different shifts. The survey sample consisted of 43 male and 11 female respondents. Personality traits were judge by a combination of tests, which included mood assessment using the ‘Positive and Negative Affect Schedule’, self-reported health using the ‘Pennebaker’s Inventory of Limbic Linguiness’, and personality assessment using the ‘State and Trait Anxiety Inventory’ (Tamagawa et al., 2007, p. 637). In the end, the researchers concluded that personality traits and moods had a significant effect on worker’s shift work tolerance. Specifically, the research observed that police officers who exhibited high anxiety levels, negative moods, repressive emotions and low positive moods were also more intolerant to shift work. In the end, Tamagawa et al. (2007) found anxiety as an influential trait that can be used a predictor of night shift tolerance, while negative or positive moods were found to be important predictors of the officer’s tolerance to rotating shifts. In their own admission, Tamagawa et al. (2007) observe that their study had several key weaknesses, which included the small size of the survey sample, the self-reported data, which was not validated using external measures, and the fact that all respondents were drawn from the same shift order.

Zhao and Turner (2008) also investigated the impact that shift work has on people health habits and outcomes through a systematic review of seventeen studies conducted on the subject area. In the literature review-based study, the researchers measured the daily health habits exhibited by people through alcohol consumption, smoking, exercise and diet indicators. To meet the objective of their research, Zhao and Turner (2008), chose an inclusion criteria that required the literature to be featured in the survey to be either observational or analytical. In addition, the respondents in all the featured literature had to be adults working on a shift basis.

To come up with the appropriate articles for review, Zhao and Turner (2008) searched through electronic databases, which included EBSCO, CINAHL, MEDLINE, and Nursing/Academic edition of Health Source. The results of the literature review indicated that shift workers, were more likely than daytime workers to engage in lifestyles that have adverse implications to their health. Specifically, the shift workers portrayed a lower intake of healthy diets compared to the daytime workers, and were more likely to smoke and engage in alcohol consumption. Zhao and Turner (2008) also identified obesity or being overweight as the most likely outcome that shift workers have after engaging in the identified lifestyles. The main weakness of this research was that Zhao and Turner (2006) could have introduced the biases of the featured researches into their own work. The two researchers also admitted that two of the articles retrieved for review were not in the English language, thus making it difficult for the researchers to understand and interpret their contents. In the end, the study found an association between shift work and the intake of unhealthy meals. Smoking was also prevalent in shift workers. However, the research could not establish the exact effect that shift work had on alcohol consumption or exercise regimens. As such, one gets the impression that Zhao and Turner’s (2006) attempt to understand the impact that shift work has on people’s health habits was not fully realized. Moreover, the researchers fail to tie the unhealthy diets concept to shift work as neatly as Kales et al. (2009) do.

According to Kales et al. (2009), the unhealthy eating habits have a connection to shift work since there are pull factors that attract the shift workers to such diets. “Expediency, convenience of fast food as a choice during work-time, and the tradition of communal meals at fire stations rich in saturated fats and simple refined carbohydrates” are some of the factors that entice shift workers into eating unhealthy diets (Kales et al. 2009, p. 13). The consequences of such diets on shift worker’s health is even made worse by sleep deprivation, which has the capacity to encourage insulin resistance in the body and metabolic syndrome further complicating the health symptoms in shift workers (Kales et al., 2009).

A comparison and a critique of the methodologies used

Apart from Zhao and Turner (2006), other articles (Karlson et al. (2009); Reinberg and Ashkenazi (2008); Shen et al. (2006); and Tamagawa, Lobb and Booth (2007) featured in this literature review used questionnaires as their main research tools. In these four studies, the researchers identified respondents, in what Pansiri (2006) describes as purposive selection. According to Pansiri (2006), purposive selection is “an important qualitative sampling method because the researcher decides which members of the society is most likely to provide the answers to the questions and then deliberately includes them in the sample (p. 230).

Despite the notable advantage, the question-based surveys experienced several limitations. First, the responses were self-reported and the researchers did not have a substantive tool to measure the accuracy of the answers provided by the respondents. As Shen et al. (2006) aptly state, the self-report measures “can be subject to inadvertent reporting biases or intentional falsifications on the part of the subjects (p. 4). Secondly, the study samples were random and did not therefore guarantee unbiased results. This is evident from the fact that the respondents were not assigned to work random shifts. As Tamagawa et al. (2007) state, one cannot exclude the possibility of an adaptation or order effect when the randomness of the survey cannot be guaranteed.

Zhao and Turner’s (2006) literature-review methodology has a fair share of limitations too. By their own admission, the two researchers included two non-English articles, which could not be understood nor analyzed. The researchers could have avoided this shortcoming by using articles in a language they fully comprehended. Further, the literature review study is bound to carry on the limitations of the featured articles. This could compound the inaccuracies contained in the initial researches.

Research methods that are most effective in the area of research

Despite the highlighted limitations of the questionnaire-based research method, it remains the most effective tool of research for this kind of study. However, it is worth noting that some effects of shift work are subjective, and the questionnaire-based research method does not adequately capture the soft-core experiences and views that are held by the respondents. As such, alternative or complementary research methods need to be used in order to capture and analyze the subjective views that respondents may want to express.

To improve the quality of findings in this type of research however, Jogulu and Pansiri (2011) suggests that researchers need to use inductive as well as deductive logic. By applying the inductive-deductive logic cycles in studies, researchers can generate theories, test their hypotheses, and provide better and more accurate deductions on the subject. The inductive-deductive logic cycles would also provide subjective interpretations of the shift worker’s experiences thus providing some plausible answers to some of the unanswered questions regarding the phenomena.

Unanswered question

Going through the articles by Karlson et al. (2009), Reinberg and Ashkenazi (2008), Shen et al. (2006), Zhao and Turner (2008), and Tamagawa, Lobb and Booth (2007), one realizes that the researchers have reasonably carried out valuable investigations on how shift work affects workers. Although the worker’s health is not solely discussed in all the five articles, the researchers have featured it as either an indicator in research (Tamagawa et al., 2007; Zhao & Turner, 2008), or a consequence of shift work (Karlson et al., 2009; Reinberg & Ashkenazi, 2008; Shen et al., 2006).

In all the articles, the researchers agree that some shift workers suffer health consequences, which are associated with disruption in normal sleeping patterns, dietary patterns, and fatigue. Reading the different articles however, one would expect the researchers to answer a seemingly simple question; how can shift work schedules be improved in order to have less or no negative health consequences on the workers? Unfortunately, this question remains unanswered. The only researchers who came close to answering the question are Tamagawa et al. (2007) who found out the personality traits and moods can be used to judge shift work tolerance levels in a person. Their study was however limited by the small research sample, and the self-reported responses collected during the survey.

In order to respond to the unanswered question, future research can build on the concepts advanced by Tamagawa et al. (2007). This time however, the study sample would need to be much larger. In addition to using questionnaires, future researchers should also consider using inductive-deductive logic as suggested by Heit and Rotello (2010). This is especially necessary since assessing the respondent’s moods or personality traits is best done by observation rather than on a self-reported questionnaire. To get qualitative data on the pre-specified question, the researcher will use selected social/organizational, behavioral and personality variables as the health predictors in the sampled shift workers. To ensure that there are no biases in the research, respondents in the survey would be required to have no prior experience in shift work. In addition, reviewing existing literature in order to determine the cause of ill health in shift workers would be necessary.

Having established elsewhere that ill health in shift workers can also be caused by subjective reasons, the researcher would also need to engage in inductive logic in order to understand the meaning of the symptoms that the shift workers present with. Finally, analyzing data collected from deductive and inductive processes would require the researcher to use a combination of statistical inference and constant comparison analysis methods.


There are vast amounts of empirical studies conducted on shift work and its relation to elevated risks of poor health. A look though literature reveals that some of this studies date back as far back as 1970s. Despite the wealth of knowledge developed in the study topic, it continues attracting the interest of researchers to date mainly because the puzzle relationship between shift work and poor health has never been completely solved.

While it is agreeable that fatigue, which is associated with sleep deprivation, and lack of enough rest is a risk factor for ill health, researchers are yet to find ways through which shift-work intolerant people can be identified before being employed for shift-related tasks. Yet, identification of shift work intolerant people is important if the ill health associated with the shift schedules are to be minimized. In the articles reviewed herein, only Tamagawa et al. (2007) attempt to identify how intolerant shift workers can be identified before being scheduled for the same. This attempt to provide a solution for a problem, which is increasingly being witnessed in the fast-paced world, forms the basis of this article’s suggestion that researchers should build on Tamagawa et al.’s research in future. This is especially essential if contemporary organizations with 24-hour schedules are to maintain dependable staff members to work on shift schedules. While this review of literature cannot guarantee that such research approach would provide a sure way of determining if workers can handle shift work without suffering negative health consequences, it is worth noting that pursuing the concept could be rewarding in the end.


Heit, E., & Rotello, C.M. (2010). Relations between inductive reasoning and deductive reasoning. Journal of Experimental Psychology, 36(3), 805-812.

Jogulu, U, D., & Pansiri, J. (2011). Mixed Methods: A Research Design for Management Doctoral Dissertations. Management Research Review, 34(6), 1-22.

Kales, S.N., Tsismenakis, A.J., Zhang, C., & Soteriades, E.S. (2009). Blood pressure in firefighters, police officers and other emergency responders. American Journal of Hypertension, 22(1), 11-20.

Karlson, B., Eek, F., Orbaek, P., & Osterberg, K. (2009). Effects on sleep-related problems and self-reported health after a change of shift schedule. Journal of Occupational Health Psychology, 14(2), 97-109.

Pansiri, J. (2006). Doing tourism research using the pragmatist paradigm: an empirical example. Tourism and Hospitality: Planning & Development, 3(3), 223-240.

Reinberg, A., & Ashkenazi, I. (2008). Internal desynchronization of circadian rhythms and tolerance to shift work. Chronobiology International, 25(4), 625-643.

Shen, J., Botly, L.C.P., Chung, S.A., Gibbs, A.L., Sabanadzovic, S., & Shapiro, C.M. (2008). Fatigue and shift work. Journal of Sleep Research, 15, 1-5.

Swenson, D.X., Waseleski, D., & Hartl, R. (2008). Shift work and correctional officers: effects and strategies for adjustment. Journal of Correctional Healthcare, 14(4), 299-310.

Tamagawa, R., Lobb, B., & Booth, R. (2007). Tolerance of shift work. Applied Ergonomics, 38, 635-642.

Zhao, I., & Turner, C. (2008). The impact of shift work on people’s daily health habits and adverse health outcomes. Australian Journal of Advanced Nursing, 25(3), 8-21.